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Long-term DCA calculator: project future value by asset weight

The long-term DCA calculator projects a monthly contribution across your chosen asset weights, then wraps it in a Monte-Carlo risk range, real purchasing power, the amount needed to hit a goal, and stress scenarios. The default mix is Nasdaq, S&P 500, CSI 300 and Hang Seng Tech — every number is editable, and it all runs in your browser.

This projects a multi-asset dollar-cost-averaging plan by combining each asset's weight, expected return and volatility into a baseline path, a Monte-Carlo range of outcomes and inflation-adjusted purchasing power, so you see a plausible spread of results rather than a single guaranteed number.

Inputs

Advanced settings (volatility, fees, inflation, rebalancing, basis, Monte-Carlo) ▾

Asset weights, returns & volatility

AssetWeightReturnVol
monthly_return = (1 + annual_return - fee_drag)^(1/12) - 1

Output

Baseline path — nominal after {y}y
Pessimistic (P5) — worst 5% of Monte-Carlo
Real purchasing power — discounted at {i} inflation
Reach goal — set a goal amount
Weighted annual assumption (target weights)—
Money-weighted return on contributions—
Final / principal—
Monte-Carlo simulates many random return paths from your volatility assumptions. The band is the 5th-95th percentile of outcomes; the solid line is the median, the dashed line your deterministic baseline.
Stacked: cumulative principal plus investment gain (nominal). The dashed line is real purchasing power after inflation.
How each asset's value builds over time given weights, returns and rebalancing.
Probability of reaching your goal by the horizon for different monthly contributions.
Hang Seng Tech has no 20-year live index history. The default uses an official backfilled / short-history proxy. To stress only the post-launch record, use the Hang Seng Tech short-history scenario below.

Solve: what monthly contribution hits my goal?

Enter a goal amount above, then solve the monthly contribution needed - both the deterministic figure and the amount for an 80% Monte-Carlo confidence.

uses the goal amount and horizon above

Scenarios & sensitivity

One-tap scenarios

Not forecasts - they shift the long-run assumptions to show how sensitive the outcome is.

Showing: baseline assumptions.

Key readings

  • Baseline path is the deterministic nominal balance from monthly compounding.
  • Pessimistic (P5) is the worst 5% of Monte-Carlo paths - a realistic downside, not a guarantee.
  • Real purchasing power discounts the nominal balance back to today.
  • Money-weighted return is solved from your contributions and final balance - closer to the felt DCA experience than a simple average.
ScenarioWeighted annual10y20y30yFinal / principal

Default historical assumptions

AssetDefault returnDefault volDefault weightBasisNote
Basis note (last reviewed 2026-06-28). Default returns use a price/index basis (ex-dividends, ex-FX, ex-fees), so SPY understates true long-run ETF total return. Default volatilities are long-run approximations, not a promise. Hang Seng Tech was only formally launched in 2020 - we do not dress it up as 20-year live history. Every number is editable.

Methodology

How it computes

  • Each asset compounds monthly; new money is added at target weights.
  • Fee drag is subtracted from each annual assumption, then converted to a monthly rate.
  • Rebalancing pushes the portfolio back to target weights; never lets it drift.
  • Monte-Carlo draws random monthly returns from your volatility and a single correlation rho to show a 5-95% range.

How not to use it

  • Not investment advice and not a promise of returns.
  • History does not predict the future - especially for short-history, high-volatility assets like Hang Seng Tech.
  • It ignores FX, taxes, premium/discount, trading halts, real cash drag and slippage.
  • For a real allocation, also pressure-test max drawdown, valuation level and cash-flow needs.

Formula, assumptions & limits

Core formula
monthly = (1 + annual_net)^(1/12) - 1, with annual_net = geometric_return - fee_drag. Arithmetic basis applies volatility drag: geo = arith - sigma^2/2.
Monte-Carlo
Portfolio-level log-normal monthly returns; portfolio sigma from per-asset volatility and a single correlation rho. Seeded, so a shared link reproduces the same chart.
Assumptions
Default returns/volatilities are long-run price-index approximations, editable per asset. Last reviewed 2026-06-28.
Limits
The deterministic baseline runs per-asset and honours the rebalancing choice; Monte-Carlo runs at the portfolio level assuming a rebalanced (fixed-weight) portfolio, so the “never rebalance” option changes only the baseline, not the risk band (no correlation matrix UI). All computation is in your browser - no network, no account, nothing stored.
Spot an error?
Email [email protected].

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Frequently asked questions

How is the projected future value calculated?
Each month your contribution is added and the running balance grows by the periodic return implied by your annual assumption. Summed across every month and blended across assets by weight, that gives the baseline path. It is the standard future value of a growing annuity applied per asset, then combined by weight.
What does the Monte-Carlo range show?
It repeatedly simulates the path using your return and volatility assumptions with random month-to-month variation, then reports a spread (for example the 5th to 95th percentile) so you see a plausible range of outcomes instead of a single line.
Why adjust for inflation?
A future balance buys less than the same number of dollars does today. Real purchasing power divides the projected value by cumulative inflation over the horizon, so the result is expressed in today's money.
What is the 'monthly amount needed to hit a goal'?
Given a target end value, horizon and return assumption, the tool solves the growing-annuity formula backwards for the contribution that reaches the goal - the required monthly investment, holding your other assumptions fixed.
Are the default assets and returns fixed?
No. The default mix and every return, volatility and weight is editable. The projections are deterministic arithmetic on the numbers you enter and are an illustration, not a forecast or a promise of returns.

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Funded-account checks

Use these three pages as a simple path: understand the rules, stress a scenario, then track consistency before a payout.

1Understand the ruleCompare challenge types, drawdown floors and payout logic.2Run a breach scenarioModel intraday vs end-of-day trailing drawdown before sizing a trade.3Track consistencyCheck whether one big day is blocking payout eligibility.
Information tool only. Every result is a deterministic calculation from the numbers you enter (the Monte-Carlo range is a probabilistic estimate). Nothing runs over the network, connects to an account, or is stored. This is not investment, trading, tax or financial advice - verify before any real decision, and at minimum also pressure-test max drawdown, valuation and cash-flow needs.